OBO Foundry dashboard analysis

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/tmp/ipykernel_328/4293058459.py:21: FutureWarning:

The `inplace` parameter in pandas.Categorical.reorder_categories is deprecated and will be removed in a future version. Reordering categories will always return a new Categorical object.

Ontologies by number of axioms

Ontologies by number of classes

Ontologies by how many ontologies use it

Different serialisations used

RDF/XML Syntax    1
Name: syntax, dtype: int64

Breakdown of used Axiom Types

	count	mean	std	min	25%	50%	75%	max
AnnotationAssertion	1	177.0	NaN	177.0	177.0	177.0	177.0	177.0
ClassAssertion	1	2.0	NaN	2.0	2.0	2.0	2.0	2.0
DataPropertyDomain	1	30.0	NaN	30.0	30.0	30.0	30.0	30.0
DataPropertyRange	1	31.0	NaN	31.0	31.0	31.0	31.0	31.0
Declaration	1	113.0	NaN	113.0	113.0	113.0	113.0	113.0
DisjointClasses	1	1.0	NaN	1.0	1.0	1.0	1.0	1.0
ObjectPropertyDomain	1	26.0	NaN	26.0	26.0	26.0	26.0	26.0
ObjectPropertyRange	1	29.0	NaN	29.0	29.0	29.0	29.0	29.0
SubClassOf	1	49.0	NaN	49.0	49.0	49.0	49.0	49.0

Breakdown of used OWL Class Expression constructs

	count	mean	std	min	25%	50%	75%	max
Class	1	219.0	NaN	219.0	219.0	219.0	219.0	219.0
DataExactCardinality	1	14.0	NaN	14.0	14.0	14.0	14.0	14.0
ObjectAllValuesFrom	1	19.0	NaN	19.0	19.0	19.0	19.0	19.0
ObjectExactCardinality	1	15.0	NaN	15.0	15.0	15.0	15.0	15.0
ObjectIntersectionOf	1	19.0	NaN	19.0	19.0	19.0	19.0	19.0
ObjectMaxCardinality	1	2.0	NaN	2.0	2.0	2.0	2.0	2.0
ObjectSomeValuesFrom	1	11.0	NaN	11.0	11.0	11.0	11.0	11.0
ObjectUnionOf	1	5.0	NaN	5.0	5.0	5.0	5.0	5.0

OBO Score (Experimental)

	ontology	score	score_dash	score_impact
0	MDO	0.285	0.571	0.0

OBO Score Summary

	count	mean	std	min	25%	50%	75%	max
score	1.0	0.285	NaN	0.285	0.285	0.285	0.285	0.285
score_dash	1.0	0.571	NaN	0.571	0.571	0.571	0.571	0.571
score_impact	1.0	0.000	NaN	0.000	0.000	0.000	0.000	0.000

OBO dependency graph